Project summary
Findings:
Twitter data
Twitter data was obtained freely through a partnership between UCSB Library and Crimson Hexagon. Before downloading, the data was queried to meet the following conditions:
Crimson Hexagon only allows 10,000 randomly selected tweets to be exported, manually, at a time in .xls format. Due to this restriction, data was manually downloaded for every 2 days in order to capture all tweets. There were around 5000 average number of daily tweets that met these conditions.
The Crimson Hexagon data did not contain all desired information, including whether or not the tweet was geotagged. To get this information we used the python twarc library to “rehydrate” the data using individual tweet ids and store the tweet information as .json files. From here we were able to remove all tweets that did not have a geotag, giving us a total of 82,876 tweets.
Here is a sample of the type of the final twitter information we obtained.
| created_at | tweet_id | full_text | user_id | user_location | geo_type | geo_coordinates | language | retweet_count | favorite_count | lat | lon |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Sun Jul 16 19:44:26 +0000 2017 | 8.866729e+17 | Little throwback to a good weekend with my best friend ❤️ Women… https://t.co/g88jsCUEoq | 603899764 | NA | Point | c(34.41472222, -119.86055556) | en | 0 | 0 | 34.41472 | -119.8606 |
| Thu Jun 11 18:45:48 +0000 2015 | 6.090690e+17 | The Santa Barbara zoo heard we were coming @suemcneel @PaisleyE @PapaCBryant http://t.co/te71EB15ok | 243511111 | Los Angeles, CA | Point | c(34.4187094, -119.6659806) | en | 0 | 1 | 34.41871 | -119.6660 |
| Tue Dec 27 03:43:43 +0000 2016 | 8.135912e+17 | I’m at @TheLarkSb in Santa Barbara, CA https://t.co/dppc1BfmRw | 2674675327 | Miami, FL | Point | c(34.4146973, -119.69048875) | en | 0 | 0 | 34.41470 | -119.6905 |
| Thu Apr 02 01:06:06 +0000 2015 | 5.834352e+17 | @maddow gays! What about discrimination on my he basis of race,gender or other grounds that would be covered be Indiana law. | 107750911 | Goleta | Point | c(34.42684843, -119.87725509) | en | 0 | 0 | 34.42685 | -119.8773 |
| Mon Mar 06 18:35:13 +0000 2017 | 8.388203e+17 | Tune in tomorrow on @travelchannel bizarrefoods to see @andrewzimmern dive for sea creatures in… https://t.co/ARmOGbESkk | 435354163 | Santa Barbara, CA | Point | c(34.42149343, -119.61077387) | en | 0 | 0 | 34.42149 | -119.6108 |
| Sun Mar 12 23:36:28 +0000 2017 | 8.410704e+17 | Just a lazy Sunday afternoon. Tea with girlfriends in my pineapple @dolcegabbana shoes #shoes… https://t.co/90HGYALhfG | 885285924 | world wide | Point | c(34.4337, -119.632) | en | 0 | 2 | 34.43370 | -119.6320 |
| Sat Dec 23 21:04:10 +0000 2017 | 9.446750e+17 | How cute is new kid, HAMILTON! sb_dawg #sbdawg #adoptdontshop @ DAWG - Dog Adoption & Welfare Group https://t.co/F1yyqWRpDk | 122980318 | Santa Barbara, CA | Point | c(34.4383965, -119.8138275) | en | 2 | 1 | 34.43840 | -119.8138 |
| Fri Feb 01 17:37:46 +0000 2019 | 1.091390e+18 | I took a tip from joelsartore and stalked this doorway for almost an hour until this girl walked out to get a shot of her cool pants. Sometimes pictures aren’t about timing as they are… https://t.co/5xyo6u89X9 | 24428202 | Los Angeles, CA | Point | c(34.42000674, -119.69690592) | en | 0 | 0 | 34.42001 | -119.6969 |
| Mon Apr 25 21:31:04 +0000 2016 | 7.247124e+17 | As long as there’s a kale salad with my fried chicken sandwich I’m totally going to feel guilt… https://t.co/7NgVd6BODI | 41173620 | Los Angeles | Point | c(34.42046328, -119.70282433) | en | 0 | 0 | 34.42046 | -119.7028 |
| Mon Jul 04 05:41:55 +0000 2016 | 7.498406e+17 | Pre Croquet meeting of the minds. @ Birnam Wood Golf Club https://t.co/jaDBdOLe5s | 96452845 | Colorado | Point | c(34.43449138, -119.61061301) | en | 0 | 0 | 34.43449 | -119.6106 |
The spatial distribution of tweets highlights areas of higher population density and tourist areas in downtown Santa Barbara. There is a single coordinate that has over 11,000 tweets reported across all years. It is near De La Vina between Islay and Valerio. There is nothing remarkable about this site so I assume it is the default coordinate when people tag “Santa Barbara” generally. The coordinate is 34.4258, -119.714.
As you zoom in on the map, clusters will disaggregate. You can click on blue points to see the tweet.